#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file LocalFeatures.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 23 août 2018
#
# TODO details

from ld2dap.core import Filter, Stack, Stacker
import numpy as np

class LocalFeatures(Filter):
    def __init__(self, features=None, patch_size=3):
        super().__init__(self.__class__.__name__)
        self.features = features
        self.patch_size = patch_size

    def _process(self, data, metadata):
        self.logger.info('Local Features Filtering')
        stacker = Stacker()

        for stack in metadata:
            self.logger.debug('{}'.format(stack))

            patches = create_patches(data[:,:,stack.begin:stack.end], self.patch_size)

            for function in self.features:
                self.logger.debug('Features function {}'.format(function.__name__))
                features = function(patches, axis=-1)
                features = cast_expand_i(features, patches.dtype)

                stacker.auto_stack(features, stack, 
                        'Local Features {} {}x{}'.format(function.__name__, self.patch_size, self.patch_size), 
                        'f^{{{}}}_{{{}\\times{}}}'.format(function.__name__, self.patch_size, self.patch_size))

        return stacker.pack()
        
def cast_expand_i(X, dtype):
    return ((X - X.min()) / (X.max() - X.min()) * np.iinfo(dtype).max).astype(dtype)

def create_patches(array, patch_size=3):
        amp = int((patch_size - 1 ) / 2)

        stack = list()
        for i in range(-amp, amp+1):
            ai = i if i > 0 else None
            bi = i if i < 0 else None
            ci = -bi if bi is not None else None
            di = -ai if ai is not None else None

            for j in range(-amp, amp+1):
                offset = np.zeros_like(array)
                #offset = np.empty(array.shape)
                aj = j if j > 0 else None
                bj = j if j < 0 else None
                cj = -bj if bj is not None else None
                dj = -aj if aj is not None else None
                offset[ai:bi, aj:bj] = array[ci:di, cj:dj]
                stack.append(offset)
        return np.stack(stack, axis=-1)